Client Report

Load Demographic Data & Prerequisites

Load Libraries and Functions

library(dataplumbr)
library(data.table)

Read Combined & Deduplicated Demographics File

wvs_anz_eto <- fread("../../data/dhs_link_char/working/wvs_anz_eto_deduplicated.csv")

Client Breakdown - Unique Counts

unique_customers <- wvs_anz_eto[, .(unique_customers = .N)]
unique_anz <- wvs_anz_eto[ids %like% "anz" & (!ids %like% "eto") & (!ids %like% "wvs"), .(anz_only = .N)]
unique_eto <- wvs_anz_eto[ids %like% "eto" & (!ids %like% "anz") & (!ids %like% "wvs"), .(eto_only = .N)]
unique_wvs <- wvs_anz_eto[ids %like% "wvs" & (!ids %like% "anz") & (!ids %like% "eto"), .(wvs_only = .N)]
unique_eto_anz <- wvs_anz_eto[ids %like% "eto" & ids %like% "anz" & (!ids %like% "wvs"), .(eto_and_anz_only = .N)]
unique_eto_wvs <- wvs_anz_eto[ids %like% "eto" & ids %like% "wvs" & (!ids %like% "anz"), .(eto_and_wvs_only = .N)]
unique_wvs_anz <- wvs_anz_eto[ids %like% "wvs" & ids %like% "anz" & (!ids %like% "eto"), .(wvs_and_anz_only = .N)]
unique_wvs_anz_eto <- wvs_anz_eto[ids %like% "wvs" & ids %like% "anz" & ids %like% "eto", .(wvs_and_anz_and_eto = .N)]

Unique Clients: 108735

Unique Anasazi: 47691

Unique ETO: 14265

Unique Web Vision: 34041

Unique ETO & Anasazi: 3659

Unique ETO & Web Vision: 5246

Unique Web Vision & Anasazi: 2115

Unique Web Vision & Anasazi & ETO 1718

Client Breakdown - Location by Services Received

Client Breakdown - Gender & Ethnicity

Get Gender Info

anz_gender <- wvs_anz_eto[ids %like% "anz", .(datasource = "anz", .N), .(gender)][order(-N)]
wvs_gender <- wvs_anz_eto[ids %like% "wvs", .(datasource = "wvs", .N), .(gender)][order(-N)]
eto_gender <- wvs_anz_eto[ids %like% "eto", .(datasource = "eto", .N), .(gender)][order(-N)]
client_gender <- rbindlist(list(anz_gender, wvs_gender, eto_gender))
client_gender_grps <- client_gender[, .(dg = paste(datasource, gender), N), .(datasource, gender)]

Get Ethnicity Info

anz_ethnic_id <- wvs_anz_eto[ids %like% "anz", .(datasource = "anz", .N), .(ethnic_id)][order(-N)]
wvs_ethnic_id <- wvs_anz_eto[ids %like% "wvs", .(datasource = "wvs", .N), .(ethnic_id)][order(-N)]
eto_ethnic_id <- wvs_anz_eto[ids %like% "eto", .(datasource = "eto", .N), .(ethnic_id)][order(-N)]
client_ethnic_id <- rbindlist(list(anz_ethnic_id, wvs_ethnic_id, eto_ethnic_id))
client_ethnic_id[ethnic_id=="" | is.null(ethnic_id) | is.na(ethnic_id), ethnic_id := "no value"]
client_ethnic_id_grps <- client_ethnic_id[, .(de = paste(datasource, ethnic_id), N), .(datasource, ethnic_id)]

Client Breakdown - Gender & Ethnicity Anasazi

library(plotly)
e <- plot_ly(data= anz_ethnic_id,
             labels = ~ethnic_id, 
             values = ~N, 
             type = 'pie', 
             textposition = 'inside', 
             textinfo = 'label+percent')
e <- layout(e, title = 'Ethnic Id Breakdown for Anasazi',
            xaxis = list(showgrid = FALSE, zeroline = FALSE, showticklabels = FALSE),
            yaxis = list(showgrid = FALSE, zeroline = FALSE, showticklabels = FALSE))

g <- plot_ly(data=anz_gender,
             labels = ~gender, 
             values = ~N, 
             type = 'pie', 
             textposition = 'inside', 
             textinfo = 'label+percent')
g <- layout(g, title = 'Gender Breakdown for Anasazi',
            xaxis = list(showgrid = FALSE, zeroline = FALSE, showticklabels = FALSE),
            yaxis = list(showgrid = FALSE, zeroline = FALSE, showticklabels = FALSE))

Client Breakdown - Gender & Ethnicity Web Vision

library(plotly)
e <- plot_ly(data= wvs_ethnic_id,
        labels = ~ethnic_id, 
        values = ~N, 
        type = 'pie', 
        textposition = 'inside', 
        textinfo = 'label+percent')
e <- layout(e, title = 'Ethnic Id Breakdown for Web Vision',
         xaxis = list(showgrid = FALSE, zeroline = FALSE, showticklabels = FALSE),
         yaxis = list(showgrid = FALSE, zeroline = FALSE, showticklabels = FALSE))

g <- plot_ly(data=wvs_gender, 
        labels = ~gender, 
        values = ~N, 
        type = 'pie', 
        textposition = 'inside', 
        textinfo = 'label+percent')
g <- layout(g, title = 'Gender Breakdown for Web Vision',
         xaxis = list(showgrid = FALSE, zeroline = FALSE, showticklabels = FALSE),
         yaxis = list(showgrid = FALSE, zeroline = FALSE, showticklabels = FALSE))

Client Breakdown - Gender & Ethnicity ETO

e <- plot_ly(data= eto_ethnic_id,
        labels = ~ethnic_id, 
        values = ~N, 
        type = 'pie', 
        textposition = 'inside', 
        textinfo = 'label+percent')
e <- layout(e, title = 'Ethnic Id Breakdown for ETO',
         xaxis = list(showgrid = FALSE, zeroline = FALSE, showticklabels = FALSE),
         yaxis = list(showgrid = FALSE, zeroline = FALSE, showticklabels = FALSE))

g <- plot_ly(data=eto_gender, 
        labels = ~gender, 
        values = ~N, 
        type = 'pie', 
        textposition = 'inside', 
        textinfo = 'label+percent')
g <- layout(g, title = 'Gender Breakdown for ETO',
         xaxis = list(showgrid = FALSE, zeroline = FALSE, showticklabels = FALSE),
         yaxis = list(showgrid = FALSE, zeroline = FALSE, showticklabels = FALSE))